How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image, export_to_video

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-I2V-A14B", torch_dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("rzgar/Wan2.2_I2V_LightX2V_Slow-Mo_Fix")

prompt = "A man with short gray hair plays a red electric guitar."
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png")

image = pipe(image=input_image, prompt=prompt).frames[0]
export_to_video(output, "output.mp4")

Wan2.2 I2V LightX2V - Slow-Motion Fix

(update: uploaded 260412 4step lora variant)

Wan_2_2_I2V_lightx2v_Distill_260412_rank_128_fp16 originally extracted from lightx2v/Wan2.2-Distill-Models wan2.2_i2v_A14b_lightx2v_4step_720p_260412.safetensors

Rank_256 & 64

Left: These LoRAs | Right: LightX2V 260412 rank_128

Left: These LoRAs | Middle: Distill | Right: Comfy-Org (SEKO) Prompts: woman sprinting - man running

Model description

The default ComfyUI Wan2.2 I2V workflow ships with LightX2V LoRAs that tend to turn scenes into slow motion:

These slow-mo fix LoRAs target that problem. More natural motion without breaking the 4-step LightX2V usage pattern and quality. In practice they also feel among the fastest-looking LightX2V-style pairs released for Wan2.2 I2V (less drag, less β€œslow-mo” pacing).

File Download
wan2.2_i2v_lightx2v_motion_fix_high.safetensors Wan2.2 I2V high noise
wan2.2_i2v_lightx2v_motion_fix_low.safetensors Wan2.2 I2V low noise

Strength: 1.0 on both Β· Steps: 4 (same idea as other LightX2V setups)

πŸ™ Acknowledgements

LightX2V

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